DocumentCode :
2969899
Title :
Combination of Genetic Algorithm and LP-metric to solve single machine bi-criteria scheduling problem
Author :
Aryanezhad, M.B. ; Jabbarzadeh, A. ; Zareei, A.
Author_Institution :
Dept. of Ind. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran
fYear :
2009
fDate :
8-11 Dec. 2009
Firstpage :
1915
Lastpage :
1919
Abstract :
This paper addresses single machine bi-criteria scheduling problem with the aim of minimizing total weighted tardiness and weighted number of tardy jobs. While weighted number of tardy jobs measures the service quality provided to customers, total weighted tardiness quantify the magnitude of lateness of each job. Therefore, considering both objectives, simultaneously, will provide the highest customers satisfaction. Both objectives are known to be NP-hard, thus, Genetic Algorithm is hired to solve the problem. Since LP-metric method is a rigorous multi-objective technique for making a combined dimensionless objective, it is used to navigate the search direction of Genetic algorithm. In this way, we can reach to some of solutions that are compatible to decision maker´s opinion while overcoming the issue of problem complexity. Finally for testing the efficiency of the proposed approach, some test problems are solved.
Keywords :
computational complexity; customer satisfaction; genetic algorithms; single machine scheduling; LP metric; NP-hard problem; customers satisfaction; genetic algorithm; rigorous multi-objective technique; service quality; single machine bi-criteria scheduling problem; tardy job; total weighted tardiness minimization; Customer satisfaction; Genetic algorithms; Gold; Industrial engineering; Job shop scheduling; Navigation; Polynomials; Quality of service; Single machine scheduling; Testing; Genetic Algorithm; LP-metric;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-4869-2
Electronic_ISBN :
978-1-4244-4870-8
Type :
conf
DOI :
10.1109/IEEM.2009.5373207
Filename :
5373207
Link To Document :
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